Diagnostic of liver diseases may be performed through analysis of liver fibrosis. Liver fibrosis refers to the accumulation in the liver of fibrous scar tissue in response to injury of the hepatocytes due to various etiologies, such as for example infection with a virus (such as hepatitis viruses HCV and HBV), heavy alcohol consumption, toxins or drugs. The evolution of the fibrosis lesion may lead to cirrhosis, a condition in which the ability of the liver to function is impaired. Treatments of liver fibrosis exist, which can slow or halt fibrosis progression, and even reverse existing liver damages. On the contrary, cirrhosis is usually thought to be non-reversible.
Liver biopsy is the historical means implemented for diagnosing liver diseases in patients. Various classifications, based on liver biopsies, are used to grade fibrosis and cirrhosis, such as, for example, Metavir and Ishak (where cirrhosis is graded). For example, using Metavir scoring classification for fibrosis, five classes (named Metavir F stages) are distinguished: F0 (no fibrosis, no scarring), F1 (portal fibrosis, minimal scarring), F2 (few septa, scarring has occurred and extends outside the areas in the liver that contains blood vessels), F3 (many septa, bridging fibrosis is spreading and connecting to other areas that contain fibrosis) and finally F4 (cirrhosis or advanced scarring of the liver). In this patent application, any citation of F0, F1, F2, F3 and F4 is made with reference to the Metavir stages.
However, since liver biopsy is invasive and expensive, non-invasive diagnosis of liver fibrosis has gained considerable attention over the last 10 years as an alternative to liver biopsy. The first generation of simple blood fibrosis tests combined common indirect blood markers into a simple ratio, like APRI (Wai et al., Hepatology 2003) or FIB-4 (Valley-Pichard et al, Hepatology 2007). The second generation of calculated tests combined indirect and/or direct fibrosis markers by logistic regression, leading to a score, like Fibrotest™ (Imbert-Bismut et al., Lancet 2001), ELF score (Rosenberg et al., Gastroenterology 2004), FibroMeter™ (Cales et al., Hepatology 2005), Fibrospect™ (Patel et al., J Hepatol 2004), and Hepascore (Adams et al., Clin Chem 2005). For example, WO2005/116901 describes a non-invasive method for assessing the presence of a liver disease and its severity, by measuring levels of specific variables, including biological variables and clinical variables, and combining said variables into mathematical functions to provide a score, often called “fibrosis score”.
However, these non-invasive diagnostic tests are not 100% accurate. Indeed, false-positive or false-negative results may occur, leading to patient misclassifications. Errors may primarily be attributed to the reference (liver biopsy) or to the construction of the test (as observed on academic data). Moreover, other sources of errors may arise from the measurement of markers or of physical data underlying the test, from the practitioner, or from the patient himself.
There is thus a need for a method for limiting the occurrence of patient misclassifications, and improving accuracy of non-invasive tests. An example of unefficacy of the prior art assumption for reliability of Fibroscan based on the AUROC is shown in Example 6: AUROCs of LSE in unreliable biopsies were not significantly different than in reliable biopsies.
WO2010/013235 describes a method for diagnosing a liver disease comprising computing a reliable score including data derived from a standard breath test and other parameters, such as, for example, physiological noise. Determining the physiological noise may include the use of an expert decision system. However, the method of WO2010/013235 is specific for a diagnostic test comprising performing a standard breath test, and cannot be adapted to other non-invasive diagnostic methods.
In Liver International ISSN1478-3223 (2008), pp 1352-1362, the Inventors published an article entitled “Evaluating and increasing the reliable diagnosis rate of blood tests for liver fibrosis in chronic hepatitis C”. It is herein emphasized that reliability is a word that has different meanings in biostatistics. In this prior art document, the terms “reliable” or “reliability” was used to define reliable diagnostic intervals (RDI). RDI deals with a more precise diagnosis in terms of fibrosis stages. Thus, instead of a broad diagnosis of F2/F3/F4 stages (the patient is diagnosed as having a fibrosis, which is significant (F2) or advanced (F3) or cirrhotic (F4), one can obtain a RDI with F3/F4 diagnosis (the patient is diagnosed as having an advanced (F3) or cirrhotic (F4) fibrosis); in this prior art document, reliability refers to diagnostic precision.
In the present invention, reliability is not related to RDI. This invention is a method and an expert system for improving the reliability of a test, and cannot be used not for defining a RDI.
It is emphasized that in this invention, contrary to the prior art document, no RDI is defined; the reliability classes depict the patients groups with different accuracy levels defined by independent predictors of accuracy. For example, in patients with renal insufficiency a diagnostic test has a significantly lower accuracy than the same test in patients with normal renal function.
Also, it is emphasized that the dispersion index described in this invention is a new index of the value dispersion of a result, especially a score, comparable to standard deviation.
There is thus a need for a method for improving the reliability of diagnostic tests.